Spatial aggregation is a key functionality of spatial analysis of geographic data that allows users to start spatial analysis from an overview perspective and then narrow down to areas of interest. In order to enable navigation of such geographic data, it is necessary to aggregate geometries to a coarse grain level (i.e., a high level) in order to provide an overview to the user.
For example, a controller of a sales pipeline may want to find out in which region of the world a product is most frequently sold. Therefore, the controller, using a data exploration software application, starts on a world-wide perspective and display the sales of the product for each country. When she identifies an important area, she narrows down to this specific area for deeper analysis at a level that is higher than a most fine-grained level. In addition, the controller may want to compare different performance metrics such as sales of a particular product across each store within a particular city. Such data traversal can be processor intensive and/or require extended periods of time—thereby hampering overall performance.